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将自己的关键点检测数据集转为coco格式后,只修改配置文件开始训练。训练能够跑起来,但是loss一直为0,按照网上的教程进行了如下修改: 第一处: mmdet/core/evalution/class_names.py 代码下的 def coco_classes() 的 return 内容改为自己数据集的类别; 第二处:mmdet/datasets/coco.py 代码下的 class CocoDataset(CustomDataset) 的 CLASSES 改为自己数据集的类别。 程序才跑起来,请问自豪兄是否有只修改配置文件的方法,不想动mmdetection里的文件。
The text was updated successfully, but these errors were encountered:
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将自己的关键点检测数据集转为coco格式后,只修改配置文件开始训练。训练能够跑起来,但是loss一直为0,按照网上的教程进行了如下修改:
第一处: mmdet/core/evalution/class_names.py 代码下的 def coco_classes() 的 return 内容改为自己数据集的类别;
第二处:mmdet/datasets/coco.py 代码下的 class CocoDataset(CustomDataset) 的 CLASSES 改为自己数据集的类别。
程序才跑起来,请问自豪兄是否有只修改配置文件的方法,不想动mmdetection里的文件。
The text was updated successfully, but these errors were encountered: